• 제목/요약/키워드: Self-Tuning Control

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A fuzzy grey predictor for civil frame building via Lyapunov criterion

  • Chen, Z.Y.;Meng, Yahui;Wang, Ruei-Yuan;Chen, Timothy
    • Computers and Concrete
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    • v.30 no.5
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    • pp.357-367
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    • 2022
  • In this paper, we propose an efficient control method that can be transformed into a general building control problem for building structure control using these reliability criteria. To facilitate the calculation of controller H∞, an efficient solution method based on Linear Matrix Inequality (LMI) is introduced, namely H∞-based LMI control. In addition, a self-tuning predictive grey fuzzy controller is proposed to solve the problem caused by wrong parameter selection to eliminates the effect of dynamic coupling between degrees of freedom (DOF) in Self-Tuning Fuzzy Controllers. We prove stability using Lyapunov's stability theorem. To check the applicability of the proposed method, the proposed controller is applied and the control characteristics are determined. The simulation assumes system uncertainty in the controller design and emphasizes the use of acceleration feedback as a practical consideration. Simulation results show that the performance of the proposed controller is impressive, stable, and consistent with the performance of LMI-based methods. Therefore, an effective control method is suitable for seismic reinforcement of civil buildings.

A Novel Self-tuning Algorithm Suitable for FLCs Utilizing Dedicated Hardwares (전용 하드웨어로 구성한 FLC에 적합한 새로운 자기동조 알고리즘)

  • ;Zeungnam Bien
    • Journal of the Korean Institute of Telematics and Electronics B
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    • v.33B no.3
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    • pp.17-27
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    • 1996
  • More fuzzy hardware are expected to be utilized in the future to construct fuzzy logic controllers (FLCs). It is hard to find an existing fuzzy hardware which is adopting advanced functions such as self-tuning algorithm in addition to the conventional inference calculation. That is mainly because conventional self-tuning algorithms designed to implement with some hardware circuits is required for fuzzy hardwares to have self-tuning capability. As a first step toward the feature, a novel self-tuning algorithm is proposed in this paper. Based on the search method, the main idea of the proposed algorithm is to detemine valid ranges of input variables of an FLC in order to maximize performance indices fo the control system. The performance indices are so ismple as to be realized by hardware circuit. in dadditon to the conventional scaling-factor adjustment, the algorithm adjusts offset values as well, which, in effect, modifies fuzzy rules of the FLC. To justify the performance of the proposed algorithm, a simulation study is executed.

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Pole placement self-tuning control of robot manipulators (극점 배치 자기 동조에 의한 로보트 매니퓰레이터 제어)

  • 이종용;양태규;이상효
    • 제어로봇시스템학회:학술대회논문집
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    • 1987.10b
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    • pp.32-35
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    • 1987
  • An adaptive control scheme has been recognized as an effective approach for a robot manipulator to track a desired trajectory in spite of the presence of nonlinearties and parameter uncertainties in robot dynamic models. In this paper, an adaptive control scheme for a robot manipulator is proposed to design the self-tuning controller which combines the pole placement with the extended linearized perturbation model. And this control scheme has two components: a feadforward control and a feedback compensation control. Based on this, the controller is demonstrated by the simulation about position control of a three-link manipulator with payload and parameter uncertainty.

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A Generalized Predictive Self-Tuning Control Using Mean Horizon Control Method (Mean Horizon 제어방식을 사용한 일반화 예측 자기동조 제어)

  • Park, Juong-Il;Chung, Jong-Dae;Park, Keh-Kun
    • Journal of the Korean Institute of Telematics and Electronics
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    • v.25 no.9
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    • pp.1039-1045
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    • 1988
  • In the original incremental generalized predictive control, the receding horizon predictive control is introduced as a control law. But in this paper, we propose a generalized predictive self-tuning control using full-valued incremental controls. The control law is a mean horizon predictive control. The effectiveness of this algorithm in a variable time delay or load disturbances environment is demonstrated by computer simulation. The controlled plant is a nonminimum phase system.

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On-line self-tuning PID power controller using fuzzy logic for CDMA cellular systems (퍼지 논리를 이용한 온라인 자기동조기능을 갖는 CDMA 셀룰러 시스템용 PID 전력제어기)

  • 김상민;한진욱;김성중
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.211-214
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    • 1997
  • This paper applies fuzzy self-tuning PID controller in DS/CDMA cellular system. Power control is essential in DS/CDMA to compensate for the differing received powers due to both the slowly varying long-term and fast varying short-term fading processes and co-channel interference. The controller proposed is adaptable for the variations of the system dynamics and especially for the variable time delay which exists in mobile radio systems. Accordingly the results is the smaller power control error, that is, the smaller average transmitting power of mobile compared with the conventional control schemes. Because interferences to the other mobiles are reduced, the capacity of CDMA can be increased.

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Implementation of Self-Tuning Fuzzy Control System for Speed Control of an Induction Motor

  • Shin, Song-Ho;Jin, Shim-Young;Lee, Oh-Keol;Lee, Joon-Tark
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.449-452
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    • 1998
  • In this paper, we implemented the variable fuzzy speed controller of an IM(induction motor) using the fuzzy control algorithms. Specially, we proposed a self-tuning technique of scale factors which could make easily the fuzzy speed controller optimize. Comparing with the conventional PI speed controller, the dynamic performances of a proposed fuzzy controller such as the reaching time, the maximum overshoot and the robustness against load disturbance were substantially improved.

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A self tuning PID controller with minimum variance (최소분산 자기동조 PID제어기)

  • Jo, Won-Cheol;Jeon, Gi-Jun
    • Journal of Institute of Control, Robotics and Systems
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    • v.2 no.1
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    • pp.14-20
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    • 1996
  • This paper presents a self tuning method of a velocity type PID controller for minimum or non-minimum phase systems with time delays. The velocity type PID control structure is determined in the process of minimizing the variance of the auxilliary output, and self tuning effect is achieved through the recursive least square algorithm at the parameter estimation stage and also through the Robbins-Monro algorithm at the stage of optimizing a design parameter. This method is simple and effective compared with other existing methods[1,2]. Numerical examples are included to illustrate the procedure and to show the performance of the control system.

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Sensorless Self-Tuning Adaptive Control of Nonlinear Modeled DC Motors Using DSP (DSP를 이용한 비선형 모델을 갖는 직류 전동기의 센서없는 자기동조 적응제어)

  • 김윤호;국윤상;유연식
    • The Proceedings of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.9 no.6
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    • pp.49-56
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    • 1995
  • In this study, self-tuning adaptive control using state observer is developed. Self-tuning adaptive controller that estimates the parameters of the system in real time and generates the optimal control signals has robust characteristic about varying load and external disturbances. In addition, state observer without sensors is applied, thus the control can be performed more quickly and exactly. Since chopper is used commonly in practical drives, the characteristics of the chopper are included in state observer algorithm, which, in turn, makes the system exact estimation. Since series type DC motor has nonlinear models, linearizing approach are investigated. to realize the proposed algorithm it requires fast calculation in real time. TMS320C31, digital signal processor, is applied to realized the adaptive control algorithms.

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Self-Tuning Gain-Scheduled Skyhook Control for Semi-Active Suspension System: Implementation and Experiment

  • Tae, Hong-Kyung;Chul, Sohn-Hyun;Ryong, Jung-Jae;Shik, Hong-Keum
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.178.4-178
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    • 2001
  • In this paper a self-tuning gain-scheduled skyhook control for semi-active suspension systems is investigated. The dynamic characteristics of a continuously variable damper including electro-hydraulic pressure control valves is analyzed. A 2-d.o.f. time-varying quarter-car model that permits variations in sprung mass and suspension spring coefficient is considered. The self-tuning skyhook control algorithm proposed in this paper requires only the measurement of body acceleration. The absolute velocity of the sprung mass and the relative velocity of the suspension deflection are estimated by using integral filters. The skyhook gains are gain-scheduled in such a way that the body acceleration and the dynamic tire force are optimized. An ECU prototype ...

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Improved Neural Network-Based Self-Tuning fuzzy PID Controller for Induction Motor Speed Control (유도전동기 속도제어를 위한 개선된 신경회로망 기반 자기동조 퍼지 PID 제어기 설계)

  • 김상민;한우용;이창구
    • The Transactions of the Korean Institute of Electrical Engineers B
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    • v.51 no.12
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    • pp.691-696
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    • 2002
  • This paper presents a neural network based self-tuning fuzzy PID control scheme with variable learning rate for induction motor speed control. When induction motor is continuously used long time, its electrical and mechanical Parameters will change, which degrade the Performance of PID controller considerably. This Paper re-analyzes the fuzzy controller as conventional PID controller structure, introduces a single neuron with a back-propagation learning algorithm to tune the control parameters, and proposes a variable learning rate to improve the control performance. Proposed scheme is simple in structure and computational burden is small. The simulation using Matlab/Simulink and the experiment using dSPACE(DS1102) board are performed to verify the effectiveness of the proposed scheme.